Results 11 to 20 of about 124,081 (292)
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 There have been many proposals to reduce constituency parsing to tagging in the literature. To better understand what these approaches have in common, we cast several existing proposals into a unifying pipeline consisting of three steps: linearization, learning, and decoding.
Amini, Afra, Cotterell, Ryan
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Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Recent analyses suggest that encoders pretrained for language modeling capture certain morpho-syntactic structure. However, probing frameworks for word vectors still do not report results on standard setups such as constituent and dependency parsing.
Vilares, David +3 more
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Scene Graph Parsing as Dependency Parsing [PDF]
Proceedings of the 2018 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long Papers), 2018 In this paper, we study the problem of parsing structured knowledge graphs from textual descriptions. In particular, we consider the scene graph representation that considers objects together with their attributes and relations: this representation has been proved useful across a variety of vision and language applications.
Alan L. Yuille +3 more
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Semantic Flow for Fast and Accurate Scene Parsing [PDF]
European Conference on Computer Vision, 2020 In this paper, we focus on designing effective method for fast and accurate scene parsing. A common practice to improve the performance is to attain high resolution feature maps with strong semantic representation. Two strategies are widely used---atrous
Xiangtai Li +6 more
semanticscholar +1 more source
To Parse or Not To Parse [PDF]
, 1998 In this paper, we reconsider the problem of specialising the vanilla meta interpreter through fully automatic and completely general partial deduction techniques. In particular, we study how the homeomorphic embedding relation guides specialisation of the interpreter. We focus on the so-called parsing problem, i.e.
Wim Vanhoof, Bern Martens
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Neural Motifs: Scene Graph Parsing with Global Context [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 We investigate the problem of producing structured graph representations of visual scenes. Our work analyzes the role of motifs: regularly appearing substructures in scene graphs.
Rowan Zellers +3 more
semanticscholar +1 more source
AAAI Conference on Artificial Intelligence, 2021 In Text-to-AMR parsing, current state-of-the-art semantic parsers use cumbersome pipelines integrating several different modules or components, and exploit graph recategorization, i.e., a set of content-specific heuristics that are developed on the basis
Michele Bevilacqua +2 more
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A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions [PDF]
arXiv.org, 2022 Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is to convert a natural language (NL) question to its corresponding structured query language (SQL) based on the evidences provided by relational databases.
Bowen Qin +11 more
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Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015 We reduce phrase-representation parsing to dependency parsing. Our reduction is grounded on a new intermediate representation, "head-ordered dependency trees", shown to be isomorphic to constituent trees. By encoding order information in the dependency labels, we show that any off-the-shelf, trainable dependency parser can be used to produce ...
Fernández González, Daniel +1 more
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Accurate Unlexicalized Parsing
Annual Meeting of the Association for Computational Linguistics, 2003 We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar.
D. Klein, Christopher D. Manning
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